• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.135-141
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• 2016

Indoor zone-based services have continuously become popular by increased prevalence of smartphones. Bluetooth and ultrasound can be used for zone detection. However, bluetooth does not guarantee precise zone detection if the signal degrades due to the obstacles. Ultrasound can be easily forged by recording sound on the smartphone. For that reason, zone detection based on ultrasound has a security hole. To remedy each limitation, we propose an advanced zone detection method, that combines bluetooth and ultrasound. An authentication server issues a one-time password to the user over bluetooth. The user generates an ultrasound signal that encodes the password. In this manner, the proposed method ensures secure and accurate zone detection.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.95-101
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• 2013

MANET has an advantage that can build a network quickly and easily in difficult environment to build network. In particular, routing protocol that uses in existing mobile environment cannot be applied literally because it consists of only mobile node. Thus, routing protocol considering this characteristic is necessary. Malicious nodes do extensive damage to the whole network because each mobile node has to act as a router. In this paper, we propose technique that can detect accurately the suspected node which causes severely damage to the performance of the network. The proposed technique divides the whole network to zone of constant size and is performed simultaneously detection technique based zone and detection technique by collaboration between nodes. Detection based zone translates the information when member node finishes packet reception or transmission to master node managing zone and detects using this. The collaborative detection technique uses the information of zone table managing in master node which manages each zone. The proposed technique can reduce errors by performing detection which is a reflection of whole traffic of network.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.279-281
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• 2015

Location awareness is an important capability for mobile-based indoor services. Those indoor services have motivated the implementation of methods that need high computational load cost and complex mechanisms for positioning prediction. These mechanisms, such as opportunistic sensing and machine learning, require more energy consumption to achieve accuracy. In this paper, we propose the Bluetooth Low Energy indoor zone detection (BLEIZOD) technique. This method exploits the concept of proximity zone to reduce the load cost and complexity. Our proposed method implements the received signal strength indicator (RSSI) function more effectively to gain accuracy and reduce energy consumption.

• Journal of Power Electronics
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• v.16 no.2
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• pp.760-768
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• 2016

Three-phase grid-connected inverters are widely applied in the fields of new energy power generation, electric vehicles and so on. Islanding detection is necessary to ensure the stability and safety of such systems. In this paper, feature recognition technology is applied and a novel islanding detection method is proposed. It can identify the features of inverter systems. The theoretical values of these features are defined as codebooks. The difference between the actual value of a feature and the codebook is defined as the quantizing distortion. When islanding happens, the sum of the quantizing distortions exceeds the threshold value. Thus, islanding can be detected. The non-detection zone can be avoided by choosing reasonable features. To accelerate the speed of detection and to avoid miscalculation, an active islanding detection method based on feature recognition technology is given. Compared to the active frequency or phase drift methods, the proposed active method can reduce the distortion of grid-current when the inverter works normally. The principles of the islanding detection method based on the feature recognition technology and the improved active method are both analyzed in detail. An 18 kVA DSP-based three-phase inverter with the SVPWM control strategy has been established and tested. Simulation and experimental results verify the theoretical analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.228-236
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• 1999

In this paper, we propose visual-based self-localization and obstacle detection algorithms for indoor mobile robots. The algorithms do not require calibration, and can be worked with only single image by using the projective invariant relationship between natural landmarks. We predefine a risk zone without obstacles for a robot, and update the image of the risk zone, which will be used to detect obstacles inside the zone by comparing the averaging image with the current image of a new risk zone. The positions of the robot and the obstacles are determined by relative positioning. The method does not require the prior information for positioning robot. The robustness and feasibility of our algorithms have been demonstrated through experiments in hallway environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.12
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• pp.5873-5877
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• 2011

In this paper, we propose a study of analysis to the mobility of object such like pedestrian in safety management zone. If unusual situation is detected in safety management zone, it's designed that previous agreed mission will be processed. By human resource, safety management zone cannot be detected continuously so that through the induction of such detection system the reliability of area can be obtained. Hence, in this paper we propose the reaction scheme to detect special situation by object detection. By using sensor based processing system proposed by this paper, the detection of mobility and unusual situation can be implemented.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.265-273
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• 2008

Video Image Processing (VIP) for traffic surveillance has been used not only to gather traffic information, but also to detect traffic conflicts and incident conditions. This paper presents a system development of gathering traffic information and conflict detection based on automatic calculation of pixel length within the detection zone on a Video Detection System (VDS). This algorithm improves the accuracy of traffic information using the automatic detailed line segmentsin the detection zone. This system also can be applied for all types of intersections. The experiments have been conducted with CCTV images, installed at a Bundang intersection, and verified through comparison with a commercial VDS product.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1787-1792
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• 2005

The join of remote sensing and GIS(Geographic Information System) could be useful in various fields of marine information and land information as well as ITS(Intelligent Transport Systems). This paper is LPF(Low Pass Filtering) for the extraction of island detection in coastal zone Iron SPOT imagery which is 10m resolution photograph. The study area is based on the southern sea in korea. Sobel operator performed the extraction of island detection in coastal zone after the LPF processing by remote sensing. And, GIS was used to generate from raster to vector data. As the result, The best way prove out the 5${\times}$5 convolution mask about the LPF processing of island detection in coastal zone. It is judged the research which it sees with the fact that the presentation of very scientific and reasonable data will be possible from the oceanic dispute will occur from the EEZ(Exclusive Economic Zone).

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.68-79
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• 1998

In this paper, we propose a model-based FDI(fault detetion and isolation) algorithm to detect and isolate fault in a linear system. The proposed algorithm is gased on an HFC(hydrid fault classifier) which consists of an FCART2(fault classifier by ART2 neural network) and an FCFM(fault classifier by fault models) which operate in parallel to isolate faults. The proposed algorithm is functionally composed of three main parts-parameter estimation, fault detection, and isolation. When a change in the system occurs, the estimated parameters go through a transition zone in which errors between the system output and the stimated output and the estimated output cross a predetermined thrseshold, and in this zone the estimated parameters are tranferred to the FCART2 for fault isolation. On the other hand, once a fault in the system is detected, the FCFM statistically isolates the fault by using the error between ach fault model out put and the system output. From the computer simulation resutls, it is verified that the proposed model-based FDI algorithm can be performed successfully to detect and isolate faults in a position control system of a DC motor.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.929-938
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• 2023

ARM processors, utilized in mobile devices, have integrated the hardware isolation framework, TrustZone technology, to implement two execution environments: the trusted domain "Secure World" and the untrusted domain "Normal World". Rootkit is a type of malicious software that gains administrative access and hide its presence to create backdoors. Detecting the presence of a rootkit in a Secure World is difficult since processes running within the Secure World have no memory access restrictions and are isolated. This paper proposes a technique that leverages the hardware based PMU(Performance Monitoring Unit) to measure events of the Secure World rootkit and to detect the rootkit using deep learning.